中国组织工程研究

中国组织工程研究 ›› 2011, Vol. 15 ›› Issue (22): 4094-4097.doi: 10.3969/j.issn.1673-8225.2011.22.025

• 骨与关节图像与影像 bone and joint imaging • 上一篇    下一篇

轮廓波及曲波和小波变换用于显微图像消噪的比较

汤  敏1，陈  峰2   

  1. 南通大学，1电子信息学院，2电气工程学院，江苏省南通市 226007
  • 收稿日期:2010-12-17 修回日期:2011-02-10 出版日期:2011-05-28 发布日期:2011-05-28
  • 作者简介:汤敏☆，女，1977年生，江苏省南通市人，汉族，2007年南京航空航天大学毕业，博士，副教授，主要从事医学图像处理及分析研究。 tangmnt@yahoo.com.cn
  • 基金资助:

    国家自然科学基金项目(61005054)；江苏省高校自然科学基础研究面上项目(09KJD510004和10KJB510020)；南通市科技项目(K2009032)；南通大学2008年度博士科研启动基金(08B15)。

Comparison of microscopy image denoising effects based on contourlet, curvelet and wavelet transform

Tang Min1, Chen Feng 2   

  1. 1School of Electronics and Information, Nantong University, Nantong  226007, Jiangsu Province, China; 2School of Electrical Engineering, Nantong University, Nantong  226007, Jiangsu Province, China
  • Received:2010-12-17 Revised:2011-02-10 Online:2011-05-28 Published:2011-05-28
  • About author:Tang Min☆, Doctor, Associate professor, School of Electronics and Information, Nantong University, Nantong 226007, Jiangsu Province, China tangmnt@yahoo.com.cn
  • Supported by:

    the National Natural Science Foundation of China, No. 61005054*; the Natural Science Foundation of Jiangsu Universities, No. 09KJD510004*, 10KJB510020*; Science and Technology Program of Nantong City, No. K2009032*; Science and Technology Research Start-up Foundation for Doctors in Nantong University, No. 08B15*

PDF

459

被引次数

12

摘要：

背景：小波变换只能反映信号的零维奇异性，无法最优表示图像中的线奇异；而且小波变换只存在3个方向，这些都显著影响了它在图像处理领域的应用效果。针对小波变换的缺点，多尺度几何分析理论正在逐步发展，轮廓波变换和曲波变换就是其中的典型代表。
目的：定性、定量地比较轮廓波、曲波和小波变换在图像消噪处理中的效果。
方法：在简要介绍3种变换基本原理的基础上，比较它们在图像消噪领域的应用，以均方误差和峰值信噪比作为定量指标评价消噪效果，并将其应用于显微镜图像的消噪处理。
结果与结论：综合定量评价指标和人眼视觉感受，曲波变换的消噪结果最佳，轮廓波变换效果次之，小波变换效果则不够理想。

关键词: 轮廓波变换, 曲波变换, 小波变换, 多尺度几何分析, 图像消噪

Abstract:

BACKGROUND: Wavelets in two-dimension are good at isolating the discontinuities at edge points, but not the smoothness along the contours. In addition, separable wavelets only capture limited directional information, which weaken their application effects on image processing. Image multiscale geometric analysis theory is developed gradually to overcome the shortcomings of wavelets mentioned above.
OBJECTIVE: To compare the microscopy image denoising effects qualitatively and quantitatively based on contourlet, curvelet and wavelet transforms.
METHODS: Based on the brief descriptions of contourlet, curvelet and wavelet transform, performance analysis and comparison were done depending on image denoising with qualitative and quantitative indices computed, e.g., mean square error and peak signal-to-noise ratio.
RESULTS AND CONCLUSION: Experimental results demonstrate that for the test Lena images and microscopy images, curvelet transform achieves the best result, while wavelet transform result is poor.

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